Targeting the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) with synthetic/designer unnatural nucleoside analogs: an in silico study

ContextSince the outbreak of COVID-19 in December 2019, it developed into a pandemic affecting all the countries and millions of people around the globe. Until now, there is no medicine available to contain the spread of the virus. As an aid to drug discovery, the molecular docking and molecular dynamic tools were applied extensively. In silico studies made it possible for rapid screening of potential molecules as possible inhibitors/drugs against the targeted proteins. As a continuation of our drug discovery research, we have carried out molecular docking studies of our 12 reported unnatural nucleosides and 14 designer Avigan analogs with SARS-CoV-2, RNA-dependent RNA polymerase (RdRp), which we want to report herein. The same calculation was also carried out, taking 11 known/under trail/commercial nucleoside drug molecules for a comparison of the binding interactions in the catalytic site of RdRp. The docking results and binding efficiencies of our reported nucleosides and designer nucleosidic were compared with the binding energy of commercially available drugs such as remdesevir and favipiravir. Furthermore, we evaluated the protein-drug binding efficiency and stability of the best docked molecules by molecular dynamic studies (MD). From our study, we have found that few of our proposed drugs show promising binding efficiency at the catalytic pocket of SARS-CoV-2 RdRp and can be a promising RdRp inhibitor drug candidate. Hence, this study will be of importance to make progress toward developing successful nucleoside-based drugs and conduct the antiviral test in the wet lab to understand their efficacy against COVID-19.MethodAll the docking studies were carried out with AutoDock 4.2, AutoDock Vina and Molegro Virtual Docker. Following the docking studies, the MD simulations were carried out following the standard protocol with the GROMACS ver. 2019.6. by applying the CHARMM36 all-atom biomolecular force field. The drug-protein interaction was studied using the Biovia Discovery Studio suite, Ligplot software, and Protein-Ligand Interaction Profiler (PLIP).